Improvements in Aircraft Final Approach Procedures

The main aim of this research is to develop different avionics navigation systems that will allow the aircrafts performing approach and landing maneuvers to do it in a more efficient way. These systems will be supported by state-of-the-art navigation technologies, such as avian radars, GBAS, and ADS-B, and by the new context provided by Performance-Based Navigation (PBN). Our developments can be employed to avoid bird strikes, to efficiently handle aircraft traffic flows or to improve the usual missed approach procedure.

To achieve this last goal, we propose adaptive approximation mechanisms based on dynamic paths, which will be applied to the case of a new type of missed approach with aircraft reinjection in the landing flow. This new type of missed approach will also be adaptable to the Point Merge System, a method for sequencing arrival flows that supports continuous descent operations.

As an alternative implementation for these systems, we considered employing deep learning techniques, based on neural networks. Once trained, the neural network should be able to provide the aircrafts with the paths to follow, replacing in this way the ATC (air traffic controller) function.

With respect our framework, we employ the Matlab/Simulink software for modeling and simulating the airspace and the final approach procedure. This work environment allows us to design and to test our developments.

Topics:

Air navigation systems
Performance-Based Navigation
Air Traffic Management (ATM)
Risk management
Deep learning and neural networks

Relevant Publications:

Manuel Lopez-Lago, Rafael Casado, Aurelio Bermudez, Jose Serna
A predictive model for risk assessment on imminent bird strikes on airport areas
Aerospace Science and Technology, Volume 62, March 2017 DOI: 10.1016/j.ast.2016.11.020
Manuel López-Lago, José Serna, Rafael Casado et al.
Present and Future of Air Navigation: PBN Operations and Supporting Technologies.
International Journal of Aeronautical and Space Sciences. 2020; 21, 451–468; https://doi.org/10.1007/s42405-019-00216-y
Guillermo Tomás Fernández, Pablo Olivas, Aurelio Bermúdez, Rafael Casado
Uso de Redes Neuronales en Procedimientos de Aproximación Final de Aeronaves
“Avances en arquitectura y tecnología de computadores. Actas de las Jornadas SARTECO 2019”; ISBN: 978-84-09-12127-4
Pablo Olivas, Guillermo Tomás Fernández, Rafael Casado, Aurelio Bermúdez
Detección de Colisiones entre Aeronaves mediante Redes Neuronales<
“Avances en arquitectura y tecnología de computadores. Actas de las Jornadas SARTECO 2019”; ISBN: 978-84-09-12127-4
Rafael Casado, Aurelio Bermúdez
Neural Network-Based Aircraft Conflict Prediction in Final Approach Maneuvers
Electronics. 2020; 9(10), 1708; https://doi.org/10.3390/electronics9101708
Rafael Casado, Manuel López-Lago, José Serna, Aurelio Bermúdez
Enhanced Missed Approach Procedure based on Aircraft Reinjection
IEEE Transactions on Aerospace and Electronic Systems. 2021; https://doi.org/10.1109/TAES.2021.3082666

People:

	Rafael Casado, PhD Associate Professor Phone number: +34 967 599200 – Ext. 2279 Email: rafael.casado@uclm.es
	Aurelio Bermúdez, PhD Associate Professor Phone number: +34 967 599 200 – Ext. 2551 Email: aurelio.bermudez@uclm.es
	María Carmona Student and I+D Email: Maria.Carmona@uclm.es